Key frameworks and libraries for building AI-powered applications.
The AI development ecosystem has matured rapidly, with frameworks and libraries for every layer of the stack. From orchestration frameworks like LangChain that manage complex LLM workflows, to provider SDKs that handle API communication, to the Hugging Face ecosystem that democratizes access to thousands of models.
Choosing the right tools depends on your use case. Quick prototypes might use LangChain for its batteries-included approach. Production systems often prefer direct SDK usage for control and reliability. Understanding the landscape helps you pick the right tool for each job.
LangChain
The most popular LLM orchestration framework. Provides chains (sequential LLM calls), agents (autonomous tool-using LLMs), memory (conversation persistence), and 700+ integrations.
LlamaIndex
Specialized for data retrieval and RAG. Connects to 160+ data sources, handles document loading, chunking, embedding, and querying. Ideal for building knowledge-base applications.
Haystack
End-to-end NLP/RAG framework from deepset. Pipeline-based architecture for search, question answering, and document processing. Strong focus on production-readiness.
OpenAI SDK
Official Python and Node.js SDKs for GPT models. Clean API for chat completions, function calling, embeddings, and assistants. The de facto standard that others follow.
Anthropic SDK
Official SDK for Claude models. Supports messages API, tool use, streaming, vision, and prompt caching. Known for its clean, well-documented design.
Hugging Face Transformers
The largest open-source ML library. 400K+ models, tokenizers, training pipelines, and inference tools. Bridges the gap between research and production for open models.
Vercel AI SDK
Frontend-first AI SDK for React/Next.js. Handles streaming responses, tool calls, and multi-step interactions in the browser. Ideal for building AI-powered web apps.
Semantic Kernel
Microsoft's AI orchestration SDK for .NET, Python, and Java. Integrates with Azure OpenAI and other providers. Enterprise-focused with plugin architecture.
Instructor & Outlines
Libraries for structured output extraction. Instructor wraps LLM calls to return validated Pydantic models. Outlines enforces output schemas at the token generation level.
Choosing Your Stack
Prototype: LangChain for speed. Production: direct SDKs for control. RAG: LlamaIndex. Web apps: Vercel AI SDK. Open models: Hugging Face. Pick based on your deployment target and team skills.
LangChainMost popular LLM orchestration framework with chains, agents, memory, and 700+ integrations.
LlamaIndexData framework for LLM applications specializing in ingestion, indexing, and retrieval.
Hugging FaceOpen-source AI platform hosting 400K+ models and the Transformers library for ML development.
SDKSoftware Development Kit โ library providing programmatic access to an AI provider's models and APIs.